EI turns raw instrument data into signed, explainable results and connects them into one trusted intelligence across your lab and pipeline. EI Flow makes the call on every run, automating in-batch decisions into signed, audit-ready reports, so analysts review only the exceptions. EI Signal reads across instruments, methods, and sites to surface drift and emerging risk before it reaches release. Both are scientist-trained, SOP-aware, LIMS-integrated, and regulatory-grade, with your scientists in the loop and in control.

Where manual review bottlenecks release or creates rework. The fastest wins are high-volume, SOP-defined workflows: QC batch release, stability, DMPK and bioanalysis, and method transfer. We help pinpoint the bottleneck slowing your pipeline most, quantify the lift, and prove it on one method, expect faster cycles, fewer errors, and lower cost per result, with every decision signed and audit-ready.

We run a short method-selection session with your team and choose one high-volume, well-specified batch method. Examples include an LC or GC-MS quant panel, an HPLC release method, or a GC-FID authenticity check. Deliverables include acceptance criteria, data connectors, and a validation plan.

Phase 1: connect instruments and LIMS.
Phase 2: configure and validate side by side against your SOP.
Phase 3: go live with review-by-exception. Expected outcomes include minutes from batch to signed report, fewer manual errors, audit-ready records, and a clear expansion roadmap. We provide hands-on enablement and change-control templates.

Yes. EI is instrument-agnostic and works with your existing fleet. It sits between your instruments and your LIMS or ELN, ingesting raw instrument output and pushing signed, audit-ready results to your records system. Deploy in the cloud for speed, on-premises for data residency or low latency, or hybrid, and your data never has to leave the environment it was generated in.

Analysts stay in control. EI uses review-by-exception: routine batches auto-sign when criteria are met, and low-confidence or rule-triggered items route to humans. Your confirmations feed back to improve future calls. We train teams and tune thresholds with you.

The Limited Sample Model (LSM) is EI's proprietary architecture, built for the reality of regulated labs: scarce data and decisions that have to hold up. Where most AI needs mountains of data, LSM reaches expert-grade accuracy from as few as 30 to 50 expert-reviewed examples. It learns from instrument data, not language, capturing your scientists' own decision logic, SOPs, and thresholds, so it stays grounded and never hallucinates. When confidence runs low, it routes to your experts instead of guessing, and every correction sharpens it through active learning. The result is production-grade AI you can stand up fast, that improves with use, and that becomes your institutional IP, accurate, traceable, and regulatory-grade.

Every model, rule set, and SOP configuration is versioned. Changes go through a controlled workflow: proposed updates are validated side-by-side against the current version, require designated approver sign-off, and are logged with who changed what, when, and why. Any version can be rolled back instantly without disrupting in-flight batches. Audit logs and change histories are exportable for QA review and regulatory inspection.